استخدام النسب المالية للتنبؤ بتعثر الشركات الصناعية الأردنية : دراسة تطبيقية

Abstract EN

This study aimed to find a model consisting of a set of financial ratios in which each ratio has its own weight that indicate its importance in discriminating between industrial distressed and non distressed firms in Jordan.

The early prediction of industrial firm's distresses warns the concerned parties that they can intervene and take corrective actions before the collapses of firm.

To achieve this, twenty seven ratios were calculated for a sample of twenty eight industrial firms, half of which had failed, from its financial statement for the fourth year following three years of losses for the purpose of analysis.

These ratios were analyzed using the statistical method known as the logistic regression to reach the best form of financial ratios that can distinguish between industrial distressed and non distressed firms in the first, second and third year before distress.

The developed model contained three financial ratios which are net working capital to owner`s equity, account receivable turnover ratio, and owner`s equity to fixed assets ratio, enabling the re-classification of industrial firms in the sample within the two groups of distressed and non distressed categories with accuracy amounted 89.3% in the year of analysis, whereas its accuracy in discriminating between the failed and the non failed firms was 67.9%, 78.6%, 74.1% in the first, second, and third years respectively before distress.

Moreover, the model`s accuracy in classifying another sample of ten firms, half of which had failed, was 90% in the first year before distress.

The study concluded with some useful recommendations.

The most important of them is the utilization of the proposed model by the companies control department, Ministry of industry & Trade, current and prospective investors and company management in order to predict financial failure of industrial companies in Jordan.

The study, also, recommended the inclusion of non financial indicators such as firm size, its age, the various economic variables,…etc, as well as financial indicators such as financial ratios when building mathematical models to predict financial failure.